Scientific Discovery: A View from the Trenches
One of the primary goals in discovery science is to understand the human scientific reasoning processes. Despite sporadic success of automated discovery systems, few studies have systematically explored the socio-technical environments in which a discovery tool will ultimately be embedded. Modeling day-to-day activities of experienced scientists as they develop and verify hypotheses provides both a glimpse into the human cognitive processes surrounding discovery and a deeper understanding of the characteristics that are required for a discovery system to be successful. In this paper, we describe a study of experienced faculty in chemistry and chemical engineering as they engage in what Kuhn would call “normal” science, focusing in particular on how these scientists characterize discovery, how they arrive at their research question, and the processes they use to transform an initial idea into a subsequent publication. We discuss gaps between current definitions used in discovery science, and examples of system design improvements that would better support the information environment and activities in normal science.
KeywordsSocio-technical information behaviors knowledge discovery
Unable to display preview. Download preview PDF.
- 1.Blake, C., Pratt, W.: Collaborative information synthesis I: A model of information behaviors of scientists in medicine and public health. Journal of the American Society of Information Science and Technology (to appear) (in press, 2006)Google Scholar
- 2.Fayyad, U., Piatetsky-Shapiro, G., Smyth, P., Uthurusamy, R.: Advances in Knowledge Discovery and Data Mining. AAAI Press, Menlo Park (1996)Google Scholar
- 4.Gardner, H.: The mind’s new science: a history of the cognitive revolution. Basic Books, New York (1985)Google Scholar
- 5.Glaser, B.G., Strauss, A.L.: The discovery of grounded theory. Strategies for qualitative research. Aldine Pub. Co., Chicago (1967)Google Scholar
- 6.Kelly, G.A.: A theory of personality: The psychology of personal constructs. Norton, New York (1963)Google Scholar
- 7.Kuhn, T.S.: The Structure of Scientific Revolutions. The University of Chicago Press, Chicago (1996)Google Scholar
- 8.Langley, P.: The Computer-Aided Discovery of Scientific Knowledge. In: Arikawa, S., Motoda, H. (eds.) DS 1998. LNCS, vol. 1532, pp. 423–452. Springer, Heidelberg (1998)Google Scholar
- 9.Rescher, N.: Peirce’s philosophy of science critical studies in his theory of induction and scientific method. University of Notre Dame Press, Notre Dame, London (1978)Google Scholar
- 10.QSR International Pty Ltd., www.qsrinternational.com/products/productoverview
- 14.Valdés-Pérez, R.E.: Some Recent Human-Computer Discoveries in Science and What Accounts or Them. AI Magazine 16(3), 37–44 (1995)Google Scholar
- 15.Zytkow, J.M.: Combining many searches in the FAHRENHEIT discovery system. In: Proceedings of the 4th International workshop on machine learning, San Mateo, pp. 281–287 (1987)Google Scholar